基于平滑A*算法的移动机器人路径规划

Mobile Robot Optimal Path Planning Based on Smoothing A* Algorithm

摘要:

栅格环境下A*算法规划出的移动机器人路径存在折线多、转折次数多、累计转折角度大等问题.为获得较优路径,提出平滑A*算法.在A*算法规划的路径基础上,遍历路径中的所有节点,当某一节点前后节点连线上无障碍物时,将延长线路的这一中间节点删除,建立平滑A*模型.仿真结果表明,平滑A*算法优于Ant(蚁群),Anytime D*算法.平滑A*算法路径长度降低约5%,累计转折次数降低约50%,累计转折角度减少30%~60%.平滑A*算法能处理不同栅格规模下、障碍物随机分布的复杂环境下移动机器人路径规划问题.

Abstract:

Path planned by A* algorithm for mobile robot under grid environment is flaw with much broken lines,frequently turning points,large cumulative turning angle.Smoothing A* is proposed in order to obtain optimum path.Based on the initial path planned by A*,traversing all the nodes on initial path,deleting the node which prolong the length of initial path as no obstacle existing on the line connected by forward and after nodes.Smoothing A* model is established after initial path processed.Simulation results show that smoothing A* exceeds Ant,Anytime D*.Length,total turning points,cumulative turning angle of path are almost reduced by 5%,50%,30%~60% respectively when smoothing A* algorithm is adopted.Path planning problem under different complex environment with random obstacles distribution can be achieved by smoothing A* algorithm.